caret v4.92

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by Max Kuhn

Classification and Regression Training

Misc functions for training and plotting classification and regression models

Functions in caret

Name Description
BoxCoxTrans.default Box-Cox Transformations
as.table.confusionMatrix Save Confusion Table Results
oneSE Selecting tuning Parameters
BloodBrain Blood Brain Barrier Data
findCorrelation Determine highly correlated variables
normalize.AffyBatch.normalize2Reference Quantile Normalization to a Reference Distribution
segmentationData Cell Body Segmentation
applyProcessing Data Processing on Predictor Variables (Deprecated)
diff.resamples Inferential Assessments About Model Performance
plot.train Plot Method for the train Class
predict.train Extract predictions and class probabilities from train objects
cars Kelly Blue Book resale data for 2005 model year GM cars
oil Fatty acid composition of commercial oils
confusionMatrix Create a confusion matrix
plotClassProbs Plot Predicted Probabilities in Classification Models
histogram.train Lattice functions for plotting resampling results
dummyVars Create A Full Set of Dummy Variables
plot.varImp.train Plotting variable importance measures
pcaNNet.default Neural Networks with a Principal Component Step
filterVarImp Calculation of filter-based variable importance
print.confusionMatrix Print method for confusionMatrix
panel.needle Needle Plot Lattice Panel
lattice.rfe Lattice functions for plotting resampling results of recursive feature selection
modelLookup Descriptions Of Models Available in train()
aucRoc Compute the area under an ROC curve
cox2 COX-2 Activity Data
format.bagEarth Format 'bagEarth' objects
classDist Compute and predict the distances to class centroids
xyplot.resamples Lattice Functions for Visualizing Resampling Results
roc Compute the points for an ROC curve
GermanCredit German Credit Data
dotPlot Create a dotplot of variable importance values
createGrid Tuning Parameter Grid
nullModel Fit a simple, non-informative model
nearZeroVar Identification of near zero variance predictors
caretFuncs Backwards Feature Selection Helper Functions
caret-internal Internal Functions
rfe Backwards Feature Selection
knn3 k-Nearest Neighbour Classification
bagEarth Bagged Earth
predict.knnreg Predictions from k-Nearest Neighbors Regression Model
prcomp.resamples Principal Components Analysis of Resampling Results
bag.default A General Framework For Bagging
resampleSummary Summary of resampled performance estimates
knnreg k-Nearest Neighbour Regression
tecator Fat, Water and Protein Content of Meat Samples
plsda Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
rfeControl Controlling the Feature Selection Algorithms
postResample Calculates performance across resamples
pottery Pottery from Pre-Classical Sites in Italy
plotObsVsPred Plot Observed versus Predicted Results in Regression and Classification Models
maxDissim Maximum Dissimilarity Sampling
print.train Print Method for the train Class
dotplot.diff.resamples Lattice Functions for Visualizing Resampling Differences
preProcess Pre-Processing of Predictors
sbfControl Control Object for Selection By Filtering (SBF)
resamples Collation and Visualization of Resampling Results
sbf Selection By Filtering (SBF)
sensitivity Calculate sensitivity, specificity and predictive values
varImp Calculation of variable importance for regression and classification models
findLinearCombos Determine linear combinations in a matrix
featurePlot Wrapper for Lattice Plotting of Predictor Variables
caretSBF Selection By Filtering (SBF) Helper Functions
trainControl Control parameters for train
train Fit Predictive Models over Different Tuning Parameters
createDataPartition Data Splitting functions
Alternate Affy Gene Expression Summary Methods. Generate Expression Values from Probes
dhfr Dihydrofolate Reductase Inhibitors Data
normalize2Reference Quantile Normalize Columns of a Matrix Based on a Reference Distribution
resampleHist Plot the resampling distribution of the model statistics
predictors List predictors used in the model
predict.knn3 Predictions from k-Nearest Neighbors
bagFDA Bagged FDA
mdrr Multidrug Resistance Reversal (MDRR) Agent Data
predict.bagEarth Predicted values based on bagged Earth and FDA models
icr.formula Independent Component Regression
summary.bagEarth Summarize a bagged earth or FDA fit
spatialSign Compute the multivariate spatial sign
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